Yifan Tong1,2, Zheyong Li1,2, Lin Ji1,2, Yifan Wang1,2, Weijia Wang3, Jiangbo Ying4, Xiujun Cai1,2. 1. Department of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China. 2. Zhejiang Provincial Key Laboratory of Laparoscopic Technology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China. 3. Department of Cardiology, Johns Hopkins Hospital, Baltimore, MD, USA. 4. National Healthcare Group, Singapore.
Abstract
BACKGROUND: Although laparoscopic liver resection (LLR) has been increasingly popular worldwide, there is lack of predictive model to evaluate the feasibility and safety of LLR. The aim of this study was to establish a scoring system for predicting the possibility of conversion and complication, which could facilitate the patient selection for clinicians and communication with patients and their relatives during the informed consent process. METHODS: Consecutively 696 patients between August 1998 and December 2016 underwent LLR were recruited. The entire cohort was divided randomly into development and validation cohorts. The scoring system for conversion and complication were established according to risk factors identified from multiple logistic analysis. Subgroup analysis was performed to assess the clinical application. And the C-index and decision curve analysis (DCA) were conducted to evaluate the discrimination in comparison with other predictive models. RESULTS: Six hundred and ninety-six patients were enrolled eventually. The rate of conversion in the development and validation cohorts was 8.3% and 10.3%, respectively. Compared with 12.6% complication rate in the development cohort, 12.9% was concluded in the validation cohort. Upon on the identified risk factors, the risk stratification model was established and validated. Subsequent subgroup analysis indicated low risk patients presented superior surgical outcomes compared with high risk patients. Besides, the C-index and DCA implied our models had better capacities of predicting conversion and complication in comparison with previous scoring systems. CONCLUSIONS: This novel scoring system presents the remarkable capacities of predicting conversion, complication in LLR. And thereby, it could be a useful instrument to facilitate the patient selection for clinicians and communication with patients and their relatives during the informed consent process.
BACKGROUND: Although laparoscopic liver resection (LLR) has been increasingly popular worldwide, there is lack of predictive model to evaluate the feasibility and safety of LLR. The aim of this study was to establish a scoring system for predicting the possibility of conversion and complication, which could facilitate the patient selection for clinicians and communication with patients and their relatives during the informed consent process. METHODS: Consecutively 696 patients between August 1998 and December 2016 underwent LLR were recruited. The entire cohort was divided randomly into development and validation cohorts. The scoring system for conversion and complication were established according to risk factors identified from multiple logistic analysis. Subgroup analysis was performed to assess the clinical application. And the C-index and decision curve analysis (DCA) were conducted to evaluate the discrimination in comparison with other predictive models. RESULTS: Six hundred and ninety-six patients were enrolled eventually. The rate of conversion in the development and validation cohorts was 8.3% and 10.3%, respectively. Compared with 12.6% complication rate in the development cohort, 12.9% was concluded in the validation cohort. Upon on the identified risk factors, the risk stratification model was established and validated. Subsequent subgroup analysis indicated low risk patients presented superior surgical outcomes compared with high risk patients. Besides, the C-index and DCA implied our models had better capacities of predicting conversion and complication in comparison with previous scoring systems. CONCLUSIONS: This novel scoring system presents the remarkable capacities of predicting conversion, complication in LLR. And thereby, it could be a useful instrument to facilitate the patient selection for clinicians and communication with patients and their relatives during the informed consent process.
Entities:
Keywords:
Laparoscopic liver resection (LLR); complication; conversion; predictive model
Authors: Roberto I Troisi; Roberto Montalti; Jurgen G M Van Limmen; Daniele Cavaniglia; Koen Reyntjens; Xavier Rogiers; Bernard De Hemptinne Journal: HPB (Oxford) Date: 2013-03-12 Impact factor: 3.647
Authors: Yuanyuan Du; Jinlin Wang; Jun Jia; Nan Song; Chengang Xiang; Jun Xu; Zhiyuan Hou; Xiaohua Su; Bei Liu; Tao Jiang; Dongxin Zhao; Yingli Sun; Jian Shu; Qingliang Guo; Ming Yin; Da Sun; Shichun Lu; Yan Shi; Hongkui Deng Journal: Cell Stem Cell Date: 2014-02-27 Impact factor: 24.633